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Sensory information processing under physical constraints

Posted on:2003-09-16Degree:Ph.DType:Dissertation
University:The Johns Hopkins UniversityCandidate:Abshire, Pamela AnnFull Text:PDF
GTID:1464390011985223Subject:Engineering
Abstract/Summary:
We analyze information processing in biological sensory organs and in engineered microsystems. We represent natural or synthetic physical structures as micro-scale communication networks, quantitatively relating function to structure under conditions of limited resources. We establish these relationships between the functional and physical levels through models for transformations on the signal, physical constraints on the system, and noise that degrades the signal. We restrict our study to systems performing sensory information processing, indicating systems that communicate sensory information rather than perform more complex computational tasks. In this context, we take information as a metric to quantify performance in a functional sense, and power as the limiting physical resource.; To illustrate our approach with specific examples, we present studies of information capacity versus energy cost of information for two linearized systems, a biological photoreceptor and a silicon adaptive photoreceptor, and for a nonlinear system, the CMOS inverter. The communication channel model for each of the photoreceptor systems is a cascade of linear bandlimiting sections followed by additive noise. We model the filters and the noise from first principles whenever possible and phenomenologically otherwise. While the photoreceptor systems are modeled as nonlinear systems whose behavior is linearized for small signals about an operating point, the inverter is modeled according to its nonlinear dynamics. The communication channel model for the CMOS inverter incorporates nonlinear differential equations in different regimes of operation and their solutions. This raises an interesting question about whether coding can improve information rates in a physical system—that is, what are the properties of a physical system that permit it to take advantage of a coding scheme? We demonstrate a fundamental connection between the run-length constraint and linearity.; We include preliminary results for several other systems, including photodiodes in an ultrathin Silicon On Sapphire technology, the diode capacitor integrator ubiquitous in an asynchronous interchip communication protocol, and the channel capacity of a linear resistor.; This comparative study is a first step towards a fundamental and quantitative understanding of the tradeoffs between system performance and associated costs such as size, reliability and energy requirements for natural and engineered sensory microsystems.
Keywords/Search Tags:Sensory, Information, Physical, Systems
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